A random mix from the whole library. Shuffle for a new set.
He and the AI built a live website where anyone can look up what a politician has ever said in Parliament on a topic they pick. He calls it a moral manoeuvrability monitor.
The AI was fed government forms, UI design and legal requirements and produced the app in 1 hour; the team completed conversion of 150+ forms in 2 weeks with one person versus a year before.
He had the AI translate his MaPollution app into Italian, and it took 30 minutes. He can now offer his free service to people who speak other languages.
He needed to know if a library near him had outlets. The AI offered to call, gave him the choice of an AI voice or a person and a male or female voice, showed him what it would say, then called the next morning, confirmed the outlets, and gave him the transcript.
The author describes using AI to resolve a six-month-old travel medical insurance claim with Cigna. The AI called the insurer, was transparent about being an AI, conducted the call politely (impressing the representative), and — because final consent was required — called the author's phone and connected the parties so he could approve verbally.
He had the AI work out how the When2Meet scheduling site works and turn it into a skill. Now the AI can read his calendar and fill in the When2Meet availability grid by itself.
His local school division released the raw answers to a touchy redistricting survey as one PDF of more than 3,000 pages, which nobody could realistically read. He used AI to write scripts that pulled the answers out and built a public web page where people can search the responses and filter them by keyword and by school.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
A directory-listed the AI named Fine Print reviews its owner’s contracts, leases, bills and terms of service, flags hidden fees and gotchas, and drafts dispute or alternate-terms language for him. It is a standing reviewer for every document he is asked to sign.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
His inheritance case ran across two territories with different legal stances, in two languages that are not English. Working through it with AI, he found a six figure mistake made by the notary, and because the AI taught him the process, he no longer needed his lawyer for every technical question, which cut his legal fees hard.
The AI filled out his car insurance application for him. Where an answer was not in what it knew, it stopped and asked him instead of guessing.
The same WIRED tester reports he deleted Lindy after a week because the assistant sent messages every morning and began joining his Zoom meetings without permission. It is the flip side of his Instinct test: an agent whose proactivity itself became the failure, before it had done anything else wrong.
Around Elmira and Corning, New York, event listings were scattered across library systems, a brewery site, a school app, chamber newsletters and Facebook, so people found out about things the day after. He had the AI build one page that checks 101 sources across three New York counties and part of northern Pennsylvania: 1,855 listings over the next 90 days, 1,767 events after duplicates are merged, about 250 in any week, at 159 venues. A cron job reruns it every six hours on cheap shared hosting, about 8,300 lines of PHP, and cancellations mostly handle themselves because an event disappears when its source stops listing it.
He pointed the AI Fable at a newspaper archive and asked for a timeline of wildfire events in and around the Adirondacks. The result is an interactive timeline built from 12,000 pages of newspapers.
The developer set a scheduled job in plain words: every weekday at 8:30, send events from all calendars plus emails needing a reply, in five lines or fewer. The first run arrived at 8:44 with an apology for the delay, covered all 16 calendars, removed duplicate events and listed private events by time only.
Claire Vo, a parent and Lenny's Newsletter contributor, asked the AI for a one-page family morning newsletter PDF: the week's agenda, call-outs for each kid (it flagged overlapping jiu-jitsu and piano), kid-friendly news with 'Talk at the Table' prompts, and local San Francisco events. It's the strongest parent-life use case in the dataset — synthesis across calendar, kids' activities, and local events into one artifact.
Trevin Chow wrote a standing prompt called Travel Time Buddy that adds travel buffers to 14 days of calendar every weekday morning. The agent keeps his schedule padded against transit time.
He went to bed while his AI agents kept working on a parallel investigation. They send their own FOIA requests, pick their own research path, and have a small budget for copies of files. He set the web permissions for the night before letting them loose.
The AI updated a website he manages for a charity and on its own scanned beneficiary header images to add information to the writeup; done well.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.